{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tushare as ts\n",
    "ts.set_token('65e7ec2a529b0af0d5e759c7dc37c57acc95bde0b4e783b8b008c420')\n",
    "pro = ts.pro_api()\n",
    "df = pro.daily(ts_code='000001.SZ', start_date='20250101', end_date='20250820')\n",
    "df.to_csv('../data/raw/000001_daily.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    },
    "pycharm": {
     "name": "#%%\n"
    }
   },
   "outputs": [],
   "source": [
    "# Cell 1：环境 & 路径\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from pathlib import Path\n",
    "\n",
    "ROOT = Path('..')\n",
    "RAW   = ROOT/'data'/'raw'\n",
    "FONT = ROOT/'fonts'\n",
    "CHART = ROOT/'charts'\n",
    "CHART.mkdir(exist_ok=True)\n",
    "\n",
    "sns.set_style('whitegrid')\n",
    "plt.rcParams['font.sans-serif'] = ['SimHei']   # 中文"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            日期  成交金额   费用        市值       总资产  净出入金\n",
      "0   2025-01-02     0  0.0  26967.00  29167.54   0.0\n",
      "1   2025-01-03     0  0.0  26625.00  28825.54   0.0\n",
      "2   2025-01-06     0  0.0  26549.00  28549.54   0.0\n",
      "3   2025-01-07     0  0.0  26706.00  28905.54   0.0\n",
      "4   2025-01-08     0  0.0  26931.00  29131.54   0.0\n",
      "..         ...   ...  ...       ...       ...   ...\n",
      "153 2025-08-14     0  0.0  19543.22  19935.26   0.0\n",
      "154 2025-08-15     0  0.0  19552.22  19944.26   0.0\n",
      "155 2025-08-16     0  0.0  19919.22  20311.26   0.0\n",
      "156 2025-08-19     0  0.0  20291.22  20683.26   0.0\n",
      "157 2025-08-20     0  0.0  21158.22  21550.26   0.0\n",
      "\n",
      "[158 rows x 6 columns]\n"
     ]
    }
   ],
   "source": [
    "# Cell 2：读净值 & 归一化\n",
    "rename_map = {\n",
    "    'date': 'date',\n",
    "    '成交日期': 'date',\n",
    "    '日期': 'date',\n",
    "    'trade_date': 'date'\n",
    "}\n",
    "# ===== 读上证指数数据 =====\n",
    "SHIndex = pd.read_csv(RAW/'000001_daily.csv', parse_dates=['trade_date'])\n",
    "SHIndex['nav'] = SHIndex['close'] / SHIndex['close'].iloc[0]   # 以首日=1 归一化\n",
    "SHIndex = SHIndex.rename(columns=rename_map)\n",
    "\n",
    "# ===== 读资产对账单（核心） =====\n",
    "# 列名：日期,成交金额,费用,市值,总资产,净出入金\n",
    "account  = pd.read_csv(RAW/'Tx_List_20250820.csv',\n",
    "                sep=None,               # 自动探测分隔符\n",
    "                engine='python',\n",
    "                skipinitialspace=True,\n",
    "                parse_dates=['日期'])\n",
    "account['日期'] = pd.to_datetime(account['日期'], errors='coerce')\n",
    "account  = account.sort_values('日期').reset_index(drop=True)\n",
    "account = account.dropna(how='all')                 # 整行全 NaN 就删除\n",
    "account = account.dropna(subset=['日期'])           # 日期解析失败删除\n",
    "\n",
    "print(account)\n",
    "\n",
    "account['pure_equity'] = account['总资产'] - account['净出入金'].fillna(0)  # 纯投资盈亏对应的日净资产\n",
    "account['day_factor'] = (account['pure_equity'] / account['总资产'].shift(1)).fillna(1)  # 计算日增长因子\n",
    "account['nav'] = account['day_factor'].cumprod()  # 生成净值序列（以日增长因子计算）\n",
    "\n",
    "account = account.rename(columns=rename_map)\n",
    "#print(account)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Cell 3：计算回撤 & 月度收益\n",
    "# eq = SHIndex.copy()\n",
    "eq = account.copy()\n",
    "eq['cummax'] = eq['nav'].cummax()\n",
    "eq['drawdown'] = (eq['nav'] - eq['cummax']) / eq['cummax']\n",
    "\n",
    "eq['month'] = eq['date'].dt.to_period('M')\n",
    "month_ret = eq.groupby('month')['nav'].apply(lambda x: x.iloc[-1]/x.iloc[0]-1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "..\\fonts\\SimHei.ttf\n"
     ]
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from matplotlib import font_manager\n",
    "# 正常显示中文\n",
    "font_path = FONT/'SimHei.ttf'  # 或 Step 1 得到的完整路径\n",
    "print(font_path)\n",
    "font_manager.fontManager.addfont(font_path)  # 重新加载\n",
    "my_font = font_manager.FontProperties(fname=font_path)\n",
    "plt.rcParams['font.family'] = my_font.get_name()\n",
    "plt.rcParams['axes.unicode_minus'] = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 700x200 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 600x250 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Cell 4：画三张图\n",
    "# 4-1 累计收益\n",
    "fig, ax = plt.subplots(figsize=(7,3))\n",
    "ax.plot(eq['date'], (eq['nav']-1)*100, color='#1f77b4')\n",
    "ax.set_title('累计收益 %'); ax.set_ylabel('收益 %')\n",
    "plt.tight_layout(); plt.savefig(CHART/'equity_curve.png', dpi=300)\n",
    "\n",
    "# 4-2 回撤\n",
    "fig, ax = plt.subplots(figsize=(7,2))\n",
    "ax.fill_between(eq['date'], eq['drawdown']*100, color='crimson', alpha=0.3)\n",
    "ax.set_title('回撤 %'); ax.set_ylabel('回撤 %')\n",
    "plt.tight_layout(); plt.savefig(CHART/'drawdown.png', dpi=300)\n",
    "\n",
    "# 4-3 月度收益\n",
    "fig, ax = plt.subplots(figsize=(6,2.5))\n",
    "month_ret.plot(kind='bar', ax=ax, color='steelblue')\n",
    "ax.set_title('月度收益 %'); ax.set_ylabel('收益 %')\n",
    "plt.xticks(rotation=0); plt.tight_layout()\n",
    "plt.savefig(CHART/'monthly_returns.png', dpi=300)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>总收益</th>\n",
       "      <th>年化收益</th>\n",
       "      <th>Sharpe</th>\n",
       "      <th>最大回撤</th>\n",
       "      <th>日胜率</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>49.9%</td>\n",
       "      <td>91.5%</td>\n",
       "      <td>2.61</td>\n",
       "      <td>-12.4%</td>\n",
       "      <td>52.2%</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     总收益   年化收益 Sharpe    最大回撤    日胜率\n",
       "0  49.9%  91.5%   2.61  -12.4%  52.2%"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Cell 5：统计表\n",
    "daily_ret = eq['nav'].pct_change().dropna()\n",
    "total_ret = eq['nav'].iloc[-1] - 1\n",
    "annual_ret = (1 + total_ret) ** (252/len(daily_ret)) - 1\n",
    "sharpe = daily_ret.mean() / daily_ret.std() * np.sqrt(252)\n",
    "max_dd = eq['drawdown'].min()\n",
    "win_rate = (daily_ret > 0).mean()\n",
    "\n",
    "stats = pd.DataFrame({\n",
    "    '总收益': [f'{total_ret:.1%}'],\n",
    "    '年化收益': [f'{annual_ret:.1%}'],\n",
    "    'Sharpe': [f'{sharpe:.2f}'],\n",
    "    '最大回撤': [f'{max_dd:.1%}'],\n",
    "    '日胜率': [f'{win_rate:.1%}']\n",
    "})\n",
    "stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0      1.000000\n",
      "1      0.988275\n",
      "2      0.978812\n",
      "3      0.991017\n",
      "4      0.998766\n",
      "         ...   \n",
      "153    1.386467\n",
      "154    1.387093\n",
      "155    1.412618\n",
      "156    1.438490\n",
      "157    1.498788\n",
      "Name: nav, Length: 158, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "print(eq['nav'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "PyCharm (trade_env)",
   "language": "python",
   "name": "trade_env"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.13.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}